An Ensemble Model for Teaching Assistant Evaluation using Classification Technique
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 12
Abstract
Teaching Assistant Evaluation is very important for every education sector for academic improvement. To improve the performance of teaching skill, criteria is increasing day by day. Due large number of data and criteria, data mining is one of the important factor. In this research work, we have used various data mining based classification techniques for classifying teaching skill. We have proposed ensemble models (CART+CHAID and ANN+BayesNet) to improve the teaching performance, but archived highest testing accuracy as 63.61% in case of ensemble of ANN and Byes Net with 80-20% training-testing partition.
Authors and Affiliations
M. Jitendra Vikas, Prof. R. Kiranmayi, T. Manohar
Keywords
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